Machine vision-based singulation verification system and method

ABSTRACT

A system and method for detecting multiple object conditions, such as side-by-side and overlapped objects, such as packages, on a conveyor. The system includes at least one machine vision system including at least one machine vision camera, at least one illumination subsystem and at least one machine vision computer. The illumination subsystem(s) is configured to illuminate a plurality of objects as they are conveyed past at least one field of view at an inspection station along a conveyor belt. Each machine vision camera is positioned to capture one or more images of the objects as the objects are conveyed past the field of view(s). Each machine vision computer is programmed to detect the presence of multiple object conditions by detecting and counting the number of edges appearing in an image of an object captured by one of the machine vision cameras. The method illuminates at least one object as it passes through the field of view, at which time at least one image of the object is captured. Next, each captured image is processed using a machine vision computer by windowing each parcel using a Region of Interest (ROI) and counting the number of edges appearing within the ROI. The presence of other than a single package condition is determined if the number of edges exceeds four.

RELATED APPLICATIONS

[0001] This application claims benefit of U.S. Provisional ApplicationSerial No. 60/178,037 filed Jan. 24, 2000, fully incorporated herein byreference.

FIELD OF THE INVENTION

[0002] The present invention relates to inspection systems and methodsand in particular, to a system and method for inspecting packages on aconveyor belt and detecting the presence of overlapped and/orside-by-side packages.

BACKGROUND OF THE INVENTION

[0003] Digital data and signal processing techniques and vision systemtechnology have tremendously advanced the ability to use computers asdata processing systems to accomplish sophisticated inspectionprocedures without human intervention. Almost every type of product canbenefit from low cost, high precision, high-speed automated inspectiontechnology derived from these new digital data and signal processingtechniques.

[0004] One such situation that has greatly benefited from high-speedinspection technology involves material handling systems. For example,packages or parcels traveling on a conveyor belt must be spaced apartfor individual tracking and tagging purposes. In this way, automatedsystems can duplicate tasks that were previously performed by humans,such as sorting parcels according to destination locations. However, inorder for such automated material handling apparatus to operateefficiently and effectively, parcels must be aligned and spaced apartfrom each other as they travel on conveyor systems. If, on the otherhand, parcels are side-by-side or overlap, then it is quite possiblethat one or more parcels will be erroneously sorted, which will resultin at least one parcel arriving at an incorrect destination. As can beappreciated, such situations incur additional costs in shipping andtime.

[0005] Accordingly, it would be advantageous to provide a system andmethod of identifying side-by-side and/or overlapped parcel conditionsto eliminate as many erroneous delivery situations as possible.Advantageously, such a system would be automated such that the majorityof parcel overlap conditions can be automatically detected without humanintervention. Preferably, such a system would utilize machine visioncameras, illumination systems, machine vision processors (computers) andinnovative image processing techniques to detect multiple objectconditions, such as side-by-side and overlap parcels on a packageconveyor.

SUMMARY OF THE INVENTION

[0006] The present invention provides a system and method for detectingthe above specified multiple object conditions, such as side-by-side andoverlapped packages on a package conveyor. The system includes at leastone machine vision system including at least one machine vision camera,such as a CCD camera, at least one illumination subsystem and at leastone machine vision computer. The illumination subsystem(s) is configuredto illuminate a plurality of parcels as they are conveyed past a machinevision camera's field of view at an inspection station along a conveyorbelt.

[0007] Each machine vision camera is positioned to capture one or moreimages of the parcels as the parcels are conveyed past the field ofview. Each machine vision computer is programmed to detect the presenceof multiple object conditions by detecting and counting the number ofedges appearing in an image of a parcel captured by one of the machinevision cameras.

[0008] The present invention also provides a novel method of detectingthe presence of multiple object conditions, such as side-by-side andoverlapped parcels on a conveyor belt conveying a plurality of parcelspast an inspection station. The method utilizes a machine vision systemhaving at least one machine vision camera to capture images of a fieldof view, at least one illumination subsystem for illuminating theparcels as they are conveyed through the field of view on the conveyorbelt and a machine vision computer for analyzing the captured images.The method of the present invention begins by illuminating at least oneparcel as it passes through the field of view. While the parcel(s) isilluminated, at least one image of the parcel is captured by at leastone of the machine vision cameras.

[0009] Blob processing is performed on the captured top view image. Aside-by-side condition is detected by counting the number ofdistinctively separated parcels. The blob processing is implemented witha size filter to eliminate any objects smaller than a specified parcelsize limit, for example a 2-inch by 2-inch area. If there is more thanone parcel that exceeds the parcel size limit, a side-by-side conditionis asserted. In addition, soft packages are manifested by theirirregular blob patterns and hence will have a larger edge blob sizethreshold used in subsequent analyses. A different edge blob sizethreshold is needed to correctly delineate soft packages since smallperturbations can be interpreted to be an overlap condition.

[0010] Each captured image is processed using the machine visioncomputer by first windowing each parcel using a Region of Interest(ROI). The processing continues by counting the number of edgesappearing in the ROI. The presence of other than a single parcelcondition is determined if the number of edges exceeds four.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] These and other features and advantages of the present inventionwill be better understood by reading the following detailed description,taken together with the drawings wherein:

[0012]FIG. 1 is a block diagram showing the exemplary components of asystem for detecting multiple parcel conditions according to the presentinvention;

[0013]FIG. 2 is schematic diagram of a first illumination subsystem forilluminating parcels on a conveyor in a vertical direction;

[0014]FIG. 3 is a schematic diagram of a second illumination subsystem,for back lighting parcels on a conveyor in a horizontal direction;

[0015]FIG. 4 is a schematic diagram of a cut-away perspective view of aninspection station including a combination of the illuminationsubsystems of FIGS. 1 and 2 and corresponding horizontal and verticalmachine vision cameras;

[0016]FIG. 5 is a schematic perspective view of an inspection stationincluding an alternative illumination subsystem and correspondinghorizontal and vertical machine vision cameras;

[0017]FIG. 6 is a schematic illustration of an example of a bounding boxused to window a parcel under inspection;

[0018]FIG. 7A is a schematic diagram of a vertical edge detector kernelwhich is useful for analyzing cartons that are oriented substantiallyvertically;

[0019]FIG. 7B is a schematic diagram of a horizontal edge detectorkernel configured to analyze cartons that are oriented substantiallyhorizontally;

[0020]FIG. 8A is a schematic diagram illustrating a double kernel edgedetector, including a steerable double vertical edge kernel foranalyzing substantially vertically directed edges of an orthogonallyoriented parcel;

[0021]FIG. 8B is schematic diagram of an edge detector including asteerable double horizontal edge kernel for analyzing substantiallyhorizontally directed edges of an orthogonally oriented parcel;

[0022]FIG. 9 is a schematic diagram illustrating a Region of Interest(ROI) including a plurality of image blobs, which are utilized toperform edge blob sortation according to one embodiment of the presentinvention;

[0023]FIG. 10 is a schematic diagram illustrating a corner blobindicative of an overlapped or piggy back situation; and

[0024]FIG. 11 is a schematic diagram illustrating an overhang blobindicative of an overlapped or piggyback package situation.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0025] Turning now to the figures, and, in particular, FIG. 1, a system10 for detecting multiple object conditions, such as side-by-side andoverlapped parcels or packages on a package conveyor, is shown. Althoughthe present invention is explained in the context of package inspection,other inspection situations can also benefit from and utilize theteachings of the present invention and are considered to be within thescope of the present invention.

[0026] The system 10 is configured to detect the presence of a varietyof parcel conditions as parcels 12 are conveyed on a package conveyor 14past an inspection station 16. The system 10 includes at least onemachine vision camera 20, an illumination subsystem 40 and at least onemachine vision computer 80. The system 10 interfaces with parcelsorting/handling equipment 18 via the machine vision computer 80.

[0027] The components of one embodiment of an illumination subsystem 40are shown in more detail in FIGS. 2 through 5. The illuminationsubsystem 40 is configured to illuminate the parcels as they areconveyed past a field of view 42 at inspection station 16 (FIG. 1). Inone embodiment, the field of view 42 is enclosed within a dark housing44 (FIG. 4). In addition, in this embodiment, two views of the parcelsbeing conveyed past the inspection station are inspected simultaneouslyby the system 10. A first view is captured by a vertical or top-mountedcamera 22, FIG. 2, which captures a vertical image of at least oneparcel as it is conveyed past the inspection station. A second view iscaptured by a horizontally mounted camera 24, FIG. 3.

[0028] The first or top view is imaged while the field of view 42 a isilluminated using a first illumination subsystem 40 a. The firstillumination subsystem 40 a is disposed intermediate the top view camera22 and a parcel 12 being inspected as it passes through the first fieldof view 42 a. One aspect of the first illumination subsystem 40 a is tomake the surface of any object passing within the field of view 42 a toappear substantially light against a substantially dark background.

[0029] In one embodiment, the first illumination subsystem 40 a iscomprised of a plurality of strobes 48, such as xenon strobes, placedsubstantially halfway or partway between the first machine vision camera22 and parcel 12. Each strobe 48 is disposed at an angle which hisselected to enhance the illumination of the surfaces of parcels 12 beingconveyed through the inspection station 16 and not the conveyor belt 14which serves as the substantially dark background. In an alternativeembodiment, an electronic shutter may be used on camera 22 in place ofstrobes 48.

[0030] In this embodiment, the second illumination subsystem 40 b isconfigured to provide a back light against which images of packages 12are captured as the packages 12 are conveyed past a second camera 24having a second field of view 42 b, which coincides with the secondillumination subsystem 40 b. In this manner, a second camera 24 capturesa side view or horizontally disposed image of the package 12. In oneembodiment, the second illumination subsystem comprises a light emittingdiode (LED) array 52. In another embodiment, a camera filter, sensitiveto a particular bandwidth, may be placed on second camera 24 for usewith corresponding lights of a particular bandwidth.

[0031] The components of another embodiment of an illumination subsystem40 are shown in more detail in FIG. 5. The illumination subsystem 40 isconfigured to illuminate the parcels as they are conveyed past a fieldof view 42 c at inspection station 16 (FIG. 1). In this embodiment, twoviews of the parcels being conveyed past the inspection station are alsoinspected simultaneously by the system 10. A first view is captured by avertical or top-mounted camera 22 that captures a vertical image of atleast one parcel as it is conveyed past the inspection station. A secondview is captured by a horizontally mounted camera such as camera 24,FIG. 3.

[0032] The top view is imaged while the field of view 42 c isilluminated using a first illumination subsystem 40 c. The firstillumination subsystem 40 c is disposed intermediate the top view camera22 and a parcel 12 being inspected as it passes through the first fieldof view 42 c. In this embodiment, the components of the illuminationsubsystem 40 c prevent interference from other lighting systems andambient light.

[0033] The first illumination subsystem 40 c includes a plurality ofgenerally high intensity lights 54, such as constant source sodium vaporlights, placed substantially halfway between the first machine visioncamera 22 and parcel 12. The intensity of the lights 54 is selected toovercome ambient light that may be present. Each light 54 is disposed inabout the same plane as the camera 22 with a slight angle of 10-15degrees, which may be adjusted to enhance the illumination of thesurfaces of parcels 12 being conveyed through the inspection station 16and not the conveyor belt 14 that serves as a substantially darkbackground for the packages.

[0034] In this embodiment, the illumination subsystem 40 c may becontrolled by a feedback mechanism with a photodiode 58 connected tomachine vision computer 80 reading the light level to automaticallymonitor and adjust the light level. In addition, the camera may includea shutter 56 instead of the use of strobes. Alternative and equivalentback lighting systems are available and considered to be within thescope of the present invention.

[0035] Utilizing the system of FIGS. 1 through 5, the present inventionprovides a novel method for detecting the presence of multiple parcelconditions as parcels are conveyed past an inspection station by aconveyor belt. In simple terms, the method comprises counting the numberof edges appearing in an image. If the number of edges appearing exceeda total of four, then there is a high probability that the imagecontains more than one package.

[0036] The method begins by illuminating at least one parcel as itpasses through a field of view at a parcel inspection station along aconveyor belt. As each parcel is illuminated, at least one image of theparcel is captured using at least one machine vision camera. Eachcaptured image is then processed by a machine vision computer to analyzeeach image and detect the presence of other than a single parcelappearing in the image.

[0037] In order to facilitate the processing act, the machine visioncomputer 80 includes image data processing software which generates atleast one Region of Interest (ROI), which is utilized to window theobject(s) under inspection in each image. This allows for fastersubsequent processing and also prevents false edge detection outside ofan object boundary. An example of an ROI is shown in the FIG. 6 whereina substantially off axis oriented carton 12 is windowed within ROI 102.The ROI is also used to adjust the threshold edges to be included in theedge counting process. If the edge size exceeds the threshold derivedfrom the boundary size, then the edge is counted.

[0038] The object(s) appearing in each image are then preliminarilyanalyzed to determine if the object(s) is other than a carton. Forexample, polyethylene or paper bags have irregular shapes and are notgeometrically well defined. Therefore, by counting the “blob” and “hole”results from a connectivity analysis, which is a technique well known inthe art, a parcel can be classified as either a carton or other parcel.

[0039] On the other hand, cartons and boxes are types of parcels withwell-defined geometric shapes. These shapes include squares, rectangles,circles, and symmetrical polygons, such as parallelograms, trapezoids,and octagonal shapes.

[0040] If an object is classified as a parcel other than a carton, thenadditional image processing techniques or even human intervention willbe employed. However, if an object is classified as a carton, a holeclosing technique is employed to make the carton appear uniformly light.Any artifacts, such as graphics, wrappers, tape and the like, that arenot light-saturated will be closed by a grayscale morphologicaltechnique, which essentially entails filling dark holes created by theartifact(s) with white pixels so that they will not manifest themselvesas edge blobs in the edge detection process.

[0041] Following the carton identification and hole filling steps, anedge detection process, as more fully explained below, will be performedto determine if a multiple object condition exists.

[0042] Since edge detection performs best when edges are presented in anorientation normal to a gradient, a concept known to those skilled inthe art as gradient steering is employed in order to select an imagethat provides the best outline of an object. With gradient steering, agradient angle of each parcel as it appears in the first image isdetermined and, depending on the angle of the object, either ahorizontal or vertical edge detector is chosen to obtain the bestoutline of the object. Of course, for some images, both vertical andhorizontal edge detection will provide similar results, accordingly, insuch cases, edge detection is performed in both the horizontal andvertical direction.

[0043] In one embodiment of the invention, a linear delineation processis used wherein an object is identified to be primarily a carton. Such aprocess utilizes a steerable outline edge detection step, performed oneach windowed object image using the gradient angle derived from thegradient angle determination step. The steerable outline edge detectionstep utilizes one of two forms of edge calculation, depending on theorientation of the carton. If the orientation of the carton is almostvertical or horizontal, then the steerable outline edge detection willapply a horizontal kernel and a vertical kernel to the windowed imagesto emphasize the edge contents within the image. This edge detection canfurther be enhanced by applying proper gain and offset to thecalculation. FIGS. 7A and 7B provide an example of vertical andhorizontal kernels applied to an edge detector analyzing an image of asubstantially horizontal/vertical carton. Applying such an edge detectorwill emphasize the edge contents while suppressing spurious noise.

[0044] Vertical and horizontal edge detectors can be used provided thecarton is aligned with the horizontal and vertical axes, plus or minus15 degrees. In other words if the gradient angle is between 0 degreesand 15 degrees or is between 75 degrees and 90 degrees, then thevertical and horizontal gradient detectors will be utilized.

[0045] However, the steerable horizontal and vertical edge detectorscannot be effectively used for substantially off axis oriented cartons,which are cartons having a gradient angle falling between 15 degrees and75 degrees. Therefore, if a carton is identified as having gradientangles which place the parcel in other than a substantially vertical ora substantially horizontal position, then a special outline edgedetector, such as a steerable, double kernel edge detector, must beemployed to emphasize the orthogonal edges of the carton. Such a doublekernel edge detector must be optimized for angles other thansubstantially vertical or substantially horizontal. A substantiallyoff-axis oriented carton and a steerable double kernel edge detector areshown in FIGS. 8A and 8B. As can be seen, the double kernel edgedetector applies a steerable double vertical edge kernel to emphasizethe substantially vertically oriented edges and a steerable doublehorizontal edge kernel to emphasize the substantially horizontallyoriented edges. Thus, the double kernel edge detection process resolvesrandom orientation of parcels.

[0046] The 15-degree threshold is derived from the minimum tolerableerrors introduced when part of the boundary features are not orthogonalto the gradient detectors. A minimum feature of 2 inches*sin(15degrees)=0.5 inches is the absolute minimum acceptable error. In otherwords, if a perfect square object aligned perfectly to the Cartesiancoordinate, the error is zero. However, as the object rotates toward the15-degree limit, the error gets bigger (losing some edge information)until it is not tolerable using the vertical and horizontal gradientdetectors. Accordingly orthogonal gradient detectors must be used tominimize the errors.

[0047] The next step in the method resolves the irregular nature ofparcels. Some parcels are not perfectly square, rectangular or circular.They include dents, frayed edges, bands, tapes and various artifactsassociated with random packaging, handling and transport. Therefore, theresults from the outline edge detection process cannot be guaranteed toprovide clean and separable outlines. Thus, there are occasions in whichsmaller artifacts appear as blobs or are stacked on top of one anotherand are therefore falsely counted. There are also cases when one or moreedges of a parcel are broken up due to weak contrast (reflectivity).Accordingly, the disclosed method provides a process designed to sortand eliminate false edge blobs.

[0048] This process is called “edge blob sortation” and uses the samebounding box provided in the initial connectivity analysis step, whereineach object is windowed or encompassed within a bounding box. Edge blobsortation identifies, orders, and analyzes edge blobs as follows: first,a blob list, including each identified blob is sorted according toproximity to a root blob. A root blob is a blob that is closest to onecorner of the bounding box. All of the blobs are then ordered dependingon their proximity to the root blob. For example, the second blob on thelist is the blob closest to the root blob. Then, a third blob isidentified as the blob closest to the second blob. The process continuesrecursively until each blob on the blob list is labeled. FIG. 9 shows anROI including five edge blobs. Edge blob 1 is the closest to thebounding box corner, and edge blobs 2, 3, 4, and 5 are ordered dependingon their proximity to the root blob and the other blobs.

[0049] The edge blob sortation continues by eliminating blobs utilizingco-linearity and proximity checks. For example, if two blobs are tooclose to each other, then a proximity check will eliminate the secondblob by distance. If two blobs form a two segment straight line, then aco-linearity check will eliminate the second blob by enclosed angle(angle between the two blobs) value. The edge blob sortation stepcontinues through the entire sorted blob list and eliminates all theredundant and false edge blobs for both vertical and horizontal outlinesof a parcel. The edge blob sortation step also checks to see if eachblob on the list meets certain qualifications, such as elongation,length to width ratio, and ratio of the area of the parcel to itsperimeter.

[0050] In addition, the algorithmic processing of the present inventioncan also detect piggy backed and overlapped parcels 62, FIGS. 10 and 11.The algorithm detects these situations by performing corner blob 64 andoverhang blob 66 checks. These checks are performed by drawing arecessed bounding box 68 around the parcels. A connectivity algorithm isemployed to find two white blobs 64/66. If there is one or more whiteblob, a piggyback (FIG. 10), overlapped or multiple parcel condition(FIG. 11) is detected.

[0051] After blob elimination, the method continues by counting theremaining blobs. A blob count of more than two is indicative of amultiple parcel condition. A count of two or less in each of thedirections will result in further analysis of the object by performingedge delineation and edge blob sortation on the image captured by thesecond camera.

[0052] Accordingly, a new and useful system and method for detecting thepresence of multiple parcel conditions as parcels are conveyed on aconveyor system is provided.

[0053] Modifications and substitutions by one of ordinary skill in theart are considered to be within the scope of the present invention whichis not to be limited except by the claims which follow.

1. A system for detecting the presence of overlapped objects on aconveyor belt conveying a plurality of objects, said system comprising:at least one machine vision system including at least one machine visioncamera, an illumination subsystem and at least one machine visioncomputer; said illumination subsystem configured to illuminate saidplurality of objects as said objects are conveyed past a field of viewat an inspection station along said conveyor belt; said at least onecamera positioned to capture images of said plurality of objects as saidobjects are conveyed past said field of view, and said at least onemachine vision computer programmed to detect the presence of multipleobject conditions by detecting and counting a number of edges appearingin an image captured by said at least one machine vision camera.
 2. Thesystem of claim 1, wherein said at least one machine vision cameraincludes first and second cameras, said first machine vision cameraoriented to capture a first image of said objects in said field of viewin a vertical direction, and said second machine vision camera orientedto capture a second image of said objects in said field of view in ahorizontal direction.
 3. The system of claim 2, wherein saidillumination subsystem includes first and second illumination sources,said first illumination source for illuminating said objects in avertical direction and said second illumination source for illuminatingsaid objects in a horizontal direction.
 4. The system in claim 3,wherein at least one of said first and second illumination sourcesincludes a lighting system configured to make said objects appear lightagainst a substantially dark background.
 5. The system of claim 4,wherein said lighting system includes at least one angled strobe lightoriented on a side of said objects coinciding with said at least onemachine vision camera.
 6. The system of claim 5, wherein said at leastone angled strobe includes a xenon strobe.
 7. The system of claim 4wherein said lighting system includes at least one high intensity lightadjustably disposed in approximately the same plane as said at least onemachine vision camera.
 8. The system of claim 7 wherein said at leastone high intensity light is a sodium vapor light.
 9. The system of claim7 further comprising a photodiode connected to said lighting system, forcontrolling the intensity of said high intensity light.
 10. The systemof claim 4, wherein said lighting system includes a back light orientedon a side of said parcels opposite said at least one machine visioncamera.
 11. The system of claim 10, wherein said backlight includes anLED (light emitting diode) array.
 12. The system of claim 10, whereinsaid at least one machine vision camera includes a filter sensitive tothe bandwidth of said lighting system.
 13. The system of claim 1 whereinsaid objects being conveyed and detected include packages.
 14. A systemfor detecting the presence of overlapped parcels on a conveyor beltconveying a plurality of parcels, said system comprising: at least onemachine vision system including at least one machine vision camera, anillumination subsystem and at least one machine vision computer; saidillumination subsystem configured to illuminate said plurality ofparcels as said parcels are conveyed past a field of view at aninspection station along said conveyor belt; wherein said at least onemachine vision camera includes first and second cameras, said firstmachine vision camera oriented to capture a first image of said objectsin said field of view in a vertical direction as said parcels areconveyed past said field of view, and said second machine vision cameraoriented to capture a second image of said objects in said field of viewin a horizontal direction as said parcels are conveyed past said fieldof view, and said at least one machine vision computer programmed todetect the presence of multiple parcel conditions by detecting andcounting a number of edges appearing in an image of an parcel capturedby said at least one machine vision camera.
 15. A method of detectingthe presence of overlapping parcels on a conveyor belt conveying aplurality of parcels past an inspection station including a machinevision system having at least one machine vision camera for capturingimages within a field of view, an illumination subsystem forilluminating said parcels as said parcels are conveyed through saidfield of view on said conveyor belt and a machine vision computer, saidoverlapping parcel detection method including the acts of: illuminatingat least one parcel as said at least one parcel passes through saidfield of view; capturing at least one image of said at least one parcelas said at least one parcel is illuminated; processing said at least onecaptured image using said machine vision computer by windowing said atleast one parcel using a Region of Interest (ROI), counting a number ofedges appearing in said ROI, and determining the presence of other thana single carton if said number of edges counted exceeds four.
 16. Themethod of claim 15 further including the act of identifying parcels asother than cartons by counting blob and hole results from a connectivityanalysis.
 17. The method of claim 16 further including the act ofclosing dark holes appearing in an image of at least one parcelidentified as a carton caused by artifacts on the carton using agrayscale morphological technique wherein said dark holes are filledwith white pixels.
 18. The method of claim 15, wherein said act ofcapturing at least one image of said at least one parcel includescapturing first and second images of at least one parcel, wherein saidfirst image is captured in a vertical direction and said second image iscaptured in a horizontal image.
 19. The method of claim 18, furtherincluding the act of determining a gradient angle of said at least oneparcel as it appears in said first image and selecting an edge detectorto obtain a best outline of said at least one parcel.
 20. The method ofclaim 18, wherein said act of counting a number of edges appearing insaid ROI is performed on each of said first and second images.
 21. Themethod of claim 19, wherein said act of counting a number of edgesappearing in said ROI includes performing a linear delineation processincluding a steerable outline edge detection on each windowed parcelimage using said gradient angle of each image.
 22. The method of claim21, wherein said steerable outline edge detection includes applying ahorizontal kernel and a vertical kernel to said windowed images toemphasize edge contents of substantially horizontal and substantiallyvertical parcels.
 23. The method of claim 21, wherein said steerableoutline edge detection includes applying a double kernel edge detectoroptimized for angles other than horizontal and vertical.
 24. The methodof claim 15, wherein said act of counting a number of edges appearing insaid at least one image includes edge blob sortation, wherein; a rootblob is identified as a blob closest to one corner of said ROI andsubsequent blobs are identified and numbered sequentially based on theirproximity to a previously identified blob until all blobs are appearingin an image are identified and numbered; each blob is analyzed todetermine if it is a part of an edge and blobs are eliminated usingproximity and co-linearity checks; a number of blobs remaining arecounted; and an overlapping parcel condition is detected if said numberof blobs remaining exceeds two in each of the two directions.